Improving edge detection and watershed segmentation with anisotropic diffusion and morphological levellings

Edge preserving smoothing and image simplification is of fundamental importance in a variety of remote sensing applications during feature extraction and object detection procedures. The construction of a pre-processing filtering tool for edge detection and segmentation tasks is still an open matter. Towards this end, this paper brings together two advanced nonlinear scale space representations, anisotropic diffusion filtering and morphological levellings, forming a processing scheme by their combination. The proposed scheme was applied to edge detection and watershed segmentation tasks. The experimental results showed that the developed scheme generated an effective pre-processing tool for automatic olive tree detection and solving watershed over-segmentation problems.